ExecuteSNF: Execute SNF(Similarity Network Fusion )

Description Usage Arguments Value References Examples

View source: R/ClusteringMethod.R

Description

SNF is a multi-omics data processing method that constructs a fusion patient similarity network by integrating the patient similarity obtained from each of the genomic data types. SNF calculates the similarity between patients using each single data type separately. The similarities between patients from different data types are then integrated by a cross-network diffusion process to construct the fusion patient similarity matrix. Finally, a clustering method is applied to the fusion patient similarity matrix to cluster patients into different groups, which imply different cancer subtypes. This function is based on the R package "SNFtool". The R package "SNFtool" should be installed. We write a function to integrate the clustering process and unify the input and output format. It is helpful for the standardized flow of cancer subtypes analysis and validation.
Please note: The data matrices are transposed in our function comparing to the original R package "SNFtools". We try to build a standardized flow for cancer subtypes analysis and validation.

Usage

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ExecuteSNF(datasets, clusterNum, K = 20, alpha = 0.5, t = 20, plot = TRUE)

Arguments

datasets

A list containing data matrices. For each data matrix, the rows represent genomic features, and the columns represent samples.

clusterNum

A integer representing the return cluster number

K

Number of nearest neighbors

alpha

Variance for local model

t

Number of iterations for the diffusion process

plot

Logical value. If true, draw the heatmap for the distance matrix with samples ordered to form clusters.

Value

A list with the following elements.

References

B Wang, A Mezlini, F Demir, M Fiume, T Zu, M Brudno, B Haibe-Kains, A Goldenberg (2014) Similarity Network Fusion: a fast and effective method to aggregate multiple data types on a genome wide scale. Nature Methods. Online. Jan 26, 2014

Examples

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data(GeneExp)
data(miRNAExp)
GBM=list(GeneExp=GeneExp,miRNAExp=miRNAExp)
result=ExecuteSNF(GBM, clusterNum=3, K=20, alpha=0.5, t=20)
result$group

taoshengxu/CancerSubtypes documentation built on Dec. 23, 2021, 7:46 a.m.